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Gong, Deukhee,Orpinas, Pamela Korean Society for Health Education and Promotion 2003 보건교육건강증진학회지 Vol.20 No.4
Childhood injuries are the primary cause of death and disability among children aged 5 to 14. Consistent practice of learned safety behaviors can reduce the occurrence of severe injuries among children. However, safety behavior concern is low among Korean-American children specifically and American children, in general. The objective of the study is to evaluate the impact of an unintentional injury prevention curriculum, Risk Watch among Korean-American children. A quasi-experimental design with a nonequivalent control group was used for the designed of the study. Two intervention and two control Korean schools in Atlanta participated in this study. The intervention consisted of weekly lessons in traffic, bicycle, pedestrian, and fire safety. One hundred and two students completed a pre-test and a post-test. The main outcomes were safety behaviors (seat belt use or helmet use), behavioral intentions, and safety knowledge. Analysis of covariance was used for the statistical analyses. Strong intervention effects were found for increasing knowledge of all safety topics in the intervention group. Additionally, statistically significant intervention effects were detected for increasing seat belt and helmet use, as well as behavioral intentions of wearing a seat belt and wearing a helmet, among pre-kindergarten and kindergarten students. For students in grades 1 and 2, intervention effects were found for increasing helmet use. Among students in grades 3 to 8, the intervention group showed statistically significant increases for seat belt use. Limitations of the study and recommendations for modifying and supporting unintentional injury prevention programs for school children are discussed.
PCA와 kNN를 이용한 얼굴 인식률 향상을 위한 연구
강득희(DeukHee Kang),이말례(Marley Lee) 한국지능시스템학회 2008 한국지능시스템학회 학술발표 논문집 Vol.18 No.2
얼굴인식은 얼굴 영역의 분리, 특징 추출, 인식의 단계로 이루어져 있다. 얼굴인식의 주된 연구는 인식률을 향상을 목적으로 하고 있다, 이를 위해 본 논문은 인식률 향상을 위하여 다양한 테스트 영상에 대해 히스토그램 평활화(Histogram equalization)를 적용한 후 PCA(Principle Component Analysis)를 사용하여 고유벡터(Eigenvector)값을 단계별로 추출하여 다양한 크기의 kNN으로 인식률을 평가하는 얼굴 인식모델을 연구하였다. 본 논문에서 연구한 기법에 따라 실험을 통해 얻은 결과를 기반으로 높은 인식률을 가진 고유벡터값과 k값을 찾을 수 있었다.
Non-Invasive Patient Registration Based on 3D Feature Points of Vein
Sunghwan Lim,Sehyung Park,Deukhee Lee 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10
Computer assisted surgical system (CASS) development is one of the most vigorously pursued research fields in biomedical engineering because of its numerous advantages. Nevertheless, patient registration is still a heavy burden for both patients and surgeons. Meanwhile, it is well known that veins can be seen under the skin in near infrared images because of the properties of hemoglobin. In this paper, we propose a novel registration method based on this principle. In our registration method, we extract feature points from veins using an infrared stereo vision system, and then match them with the feature points extracted from preoperative medical images. Experiments were performed to verify the feasibility of this vein-based registration. As a result, we confirmed the availability of our proposed method, and showed that it can be utilized for numerous applications.